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        <h4 class="modal-title" id="myModalLabel">Important Information</h4>
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  <b>This web portal is for research purposes only. The algorithm has not been validated for clinical use.</b><br><br>
  The portal relates to the publication:  <a href="http://dx.doi.org/10.1038/ng.3756">Gerstung et al., Precision oncology for acute myeloid leukemia using a knowledge bank approach. Nature Genetics, 49:332-340, 2017</a>. <br><br>
  It was developed on a cohort of 1,540 intensively treated patients with acute myeloid leukaemia, enrolled in three trials (AMLHD-98A, n=627;  AMLHD-98B, n=173; and AMLSG-07/04, n=740). 
  The median age of patients was 50 (40-57 inter quartile range, min 18, max 84). Median ECOG performance was 1 (0-2 inter quartile range). 
  A panel of 111 cancer genes was profiled in addition to cytogenetic data and diagnostic blood counts (<a href="http://dx.doi.org/10.1056/NEJMoa1516192">Papaemmanuil et al., New England Journal of Medicine, 374:2209-21, 2016</a>). <br><br>
  Together these data were correlated with disease outcomes using a multistage model, where each individual transition was modelled as a regularised Cox proportional hazards model.
  The accuracy (concordance) of predictions for overall survival is C=0.72 (leave one out cross-validation), C=0.70 (avg. inter-trial cross validation) and C=0.70 (TCGA, n=176, external validation). 
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  The algorithm has not been prospectively validated and treatment options (haematopoietic stem cell transplants) were not randomised.<br><br>
  By using this web portal you <b>confirm that you understand the limitations of this research tool</b>.  </p>
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